Import AI: Issue 1: GANs, ML bias, and a neural net Benjamin Franklin

by Jack Clark

Adversarial training / generative adversarial networks: “the most interesting idea in the last 10 years in ML”says Yann Lecun, a jazz aficionado who has a day job as Facebook’s Director of AI Research. One problem withGANs is that they are quite unstable and choosing the right settings is currently mostly an act of intuition, kind of like convolutional networks were a decade ago. Onward!

“It’s not my fault my data contains bias” is the new “the dog ate my homework”. Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings? –research from Boston University & Microsoft Research.

Now we knowGoogle has used reinforcement learning to reduce the power consumption of its data centers it’s reasonable to wonder how else RL can and will be applied. Answers so far includerobotics, wildfire suppression, healthcare,and more. RL will eventually be used to simulate (and run) complex multi-agent environments, like the power grid. Electric Power Market Modeling With Multi-Agent Reinforcement Learning gives somegood clues.

Layer normalization: newtechnique substantially reduces training time of recurrent nets. On one question-answering task it “trains faster but converges to a better validation result”. Which sounds suspiciously like ‘having cake and eating it too’. From University of Toronto & Google/UofT’s Geoff Hinton. Try it for yourself via thisTensorFlow implementation.

The Machine Intelligence Research Institute hasaccomplished a lot in the last year as it grapples with the paradoxes of controlling superintelligence. Its greatest achievement, though, is the invention of the term “Vingean Reflection”.

Riddle me this: ““Joan made sure to thank Susan for all the help she had given. Who had given the help? Answer 0: Joan or Answer 1: Susan””. You probably got this right. A computer would probably get this wrong, according to the latest results of theWinograd Schema Challenge.

You should follow@smilevector on twitter. It’s an experiment from Tom White that uses modern AI techniques to manipulate faces. It certainly cheered upBenjamin Franklin! (Though I’m less sure aboutObama.

Thanks for reading. If you have suggestions, comments or other thoughts you can reach me at jack@jack-clark.net or tweet at me@jackclarksf